UAV Drone Mapping of Rhizoctonia bare patch for targeted treatment by Andrea Hills, Presented at SPAA Conference Sep 2016, GRDC.

1. UAV Mapping of
Rhizoctonia bare
patch for targeted
treatment
Rhizoctonia mapping team
Andrea Hills, Phil Goulding, Lachlan
Beveridge, Daniel Huberli & Geoff Thomas

2. Rhizoctonia bare patch
Causes significant damage to cereals and pulse crops
• Attacks roots
• Stunts plant growth
• Significantly reduces yield within
patches
Photos:
Cereal roots - GRDC Rhizoctonia FactSheet, 2012
Lupin roots – Geoff Thomas DAFWA, 2016
Taproots intact
Taproots cut off

3. Rhizoctonia bare patch in cereals
Causes significant damage to cereals and pulse crops
Rhizoctonia bare patch damage in barley; Mark Adams, South Stirlings 2015

4. Mapping rhizoctonia bare patch
• A disease that reduces grain yield
• Variable distribution across paddocks
• No method to assess loss
• Fungicidal control is relatively expensive ($18 – 24/ha)
when used as a blanket application
• Fungicide must be applied at sowing
• Limited knowledge of its recurrence across seasons
The problem:

5. Rhizoctonia bare patch
Why map?
• Quantify the patch area in paddocks
• Patch distribution is uneven - identify the worst areas
• GPS location of patches
• Study the pattern of recurrence across seasons
Formulate a georeferenced treatment map for
use at sowing

6. Our approach
• UAV – normal (RGB) and/or NDVI images of paddocks
• In cereal crops in 2014 & 2015
• Ground-truthed patches – root & soil assessments
• GIS and experimental software “RhizoDetector”
• Treatment maps eg. AgLeader SMS
Tools:

7. Study paddock – Cascade, NW Esperance
40ha study area

8. Can we identify rhizoctonia on images?
Yes

9. Mapping patches using GIS
Digitising by hand using RGB or NDVI images
…time consuming work: in 2015 the 40ha study area had >3,400 patches

10. Rhizoctonia maps at a paddock scale
2015 - barley
• 2.5% of the total area
affected by rhizoctonia

11. Rhizoctonia patches over two seasons
2014 & 2015
Areas of patch overlap
• 30% area affected in
2014 reappeared in the
same position in 2015
• Increased intensity in
worst areas rather than
new areas being affected

12. New tool needed – no manual digitising

13. Tool development
RhizoDetector software
• Developed by project partners ThinkSpatial
• Automatically detects patches
• Result is a spatial file to use for treatment mapping
• Developed with Free Open Source Software

14. Tool development
RhizoDetector – auto patch mapper
• Uses NDVI to detect all areas of poor crop growth
• Selects rhizoctonia patches based on adjustable parameters
of size and roundness
50 m

15. Tool development
RhizoDetector – auto patch mapper
• The user can change the parameters of size and
roundness
Roundness 0.02Roundness 0.01 Roundness 0.03 Roundness 0.04
-
• User friendliness to be improved

16. RhizoDetector current interface
Step 2 & 3
Area and Roundness
filters
(1=perfect circle)
Zoom in/out paddock
NDVI image highlights the
areas identified as
rhizoctonia patches (to be
enlarged)
Step 1 NDVI values pick
out areas of crop growth
below a given value (will
have defaults)

17. Creating treatment maps

18. Creating treatment maps
Various approaches need testing
• Rhizoctonia treatment is
liquid fungicide at
sowing
• Simplest method applies
fungicide where
rhizoctonia was last
detected
• This method would
require sectional control
on the seeding bar
• But remember: patches
can change

19. Accommodating patch change
Patch + buffer area
treatments
• Apply buffers directly
around patches
• Requires sectional
control

20. Treatment approach 3.
KISS: no sectional control
• Break paddock into grids based on
sowing tramlines
• Assume we apply fungicide in a 12 x 5m
area (width of a seeding bar)
• Calculate rhizoctonia present as a % of
the grid – 10% is the breakeven point for
fungicide costs
• Grids provide a buffer area and
capture potential patch movement
12m
5m
>20% 2-5%
<1%10-20%
Untreated

21. Creating treatment maps
Paddock gridded & categorised (% of rhizoctonia present)
• All grids: 12.8ha treated
(not 40ha)
• >10% rhizoctonia:
2ha treated
• >5% rhizoctonia:
4.7ha treated
• One fungicide
rate or two?

22. Rhizoctonia mapping for targeted treatment

23. Rhizoctonia mapping for targeted treatment
• Use UAV images to identify and map rhizoctonia
• Identify areas of a paddock worst affected
• Quantify rhizoctonia area
We can:
Next steps:
• Continue studying how rhizoctonia behaves
• Fine tune “RhizoDetector”
• Test the effectiveness of different treatment maps

24. Thank you
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Important disclaimer
The Chief Executive Officer of the Department of Agriculture and Food and the State of
Western Australia accept no liability whatsoever by reason of negligence or otherwise
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Copyright © Western Australian Agriculture Authority, 2016
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